ournalism - “the collection, preparation, and distribution of news and related commentary” (according to Britannica). The news can be distributed in the form of newspapers, books, magazines, blogs, etc. (basically all forms of printed and electronic communication).
Journalism, now, has been exposed to various new technologies, however, the most impactful (and the one with the most prospect) is AI. Journalism has already been affected by this technology; To understand how AI has been transforming journalism, we first have to understand the journalism career, and how journalists do their job.
Being a journalist means having the ability to collect data, analyze it, and process it to deliver an appealing, readable piece to the general public. A journalist not only has to be able to search for clues and investigate, but their stories have to be intriguing, informative, and true. These articles also have to include different linguistic features, emotive language, lexis that suit the prompt, and appropriate structure. With so many conditions and exceptions, you may ask how AI can be of any help to journalists, and how AI is able to transform the field of journalism? To give you a glimpse of how human-like AI can be effectively used, here is an article written by GPT-3.
We won’t be going into the depths of AI, but we’ll be observing how AI is impacting journalism and what the future of journalism might look like.
Today’s World of Automated Journalism
Back in 2014, the Los Angeles Times published a report about an earthquake that occurred, about three minutes after it happened thanks to the help of Quakebot. This software robot analyses data from sources like the US Geological Survey and creates articles or reports about certain incidents. Today, many media organizations including the Los Angeles Times have their own AI software. The Washington Post has Heliograph and a third of the content published by Bloomberg is created through Cyborg. To know what humans want to hear, AI is analyzing vast amounts of data and coming up with different conclusions. For example, Alibaba’s e-commerce platform is enormous. As content-based platforms are becoming more popular, Alibaba has created an AI that describes products and enriches the user experience. This example is not specifically related to journalism, but it gives a clearer understanding of how content is being portrayed and tailored to the majority’s interest.
As you have probably inferred by now, AI is an integral part of journalism and media. However, AI is only limited to analyzing data and generating an objective article based on this data. This limitation requires AI and journalists to work hand in hand because some articles require opinions and a certain point of view.
AI with Opinions
IBM developed its Project Debater. This machine can debate any topic. Its concept of opinion is already being established throughout IBM. If this concept were to spread to journalism, journalists would not have to do much to write a compelling article. Adding an opinion can expand the scope of the types of articles AI can write about. If you want to know more about the Project Debater, click here.
AI and Fake News
AI not only helps journalists by creating articles faster, but AI can also help with identifying fake news. In today’s world, it is difficult to distinguish between fake and real news because news is so fast-paced which makes it difficult to know whether the information is true or not. AI systems are able to identify articles that have been artificially generated and those that have an actual data source. With this ability, newsrooms can debunk falsities. They can add links that help in identifying if the article is true or not.
Taking down articles isn’t the only use of AI in curbing the spread of fake news. The comments and responses by readers of fake news can be weeded out with the help of AI and machine learning. AI systems are being employed by social media platforms to moderate comments and posts, to prevent the spread of false or misinformation.
As AI is good with data, it can help plan new operations by finding the best choices during operations, which reduce costs and take less time to accomplish. These AI systems can use natural language processing to scan receipts and analyze paperwork, helping it come up with a solution that is both time-conserving and least expensive. On top of these two advantages, AI can do this feat in seconds.
While scanning and analyzing data, AI systems can spot unusual expenses and operations that are running outside the determined acceptable requirements. The amount of versatility AI has in journalism is enormous. It can completely change the industry if used effectively.
Advantages of AI in Journalism
- Routine Reporting - Automating routine reporting maximizes the coverage of what the press can report about. The Associated Press automated its routine reporting on companies and expanded the number of reports they can make, going from 300 to 4000 companies. With the ability to make more company reports, the market strengthened because of an increase in trading.
- Data Handling - This advantage is similar to the previous one. Creating any type of report that relies solely on data will be much faster to make with AI. AI can instantly react to real-time data. Quarterly reports released by large mutual funds would take forever to draft. A small team of portfolio managers would take weeks to draft the report. However, AI will only take seconds to draft the same report. As the data changes, the report gets updated in real-time by the AI. Reuters is one of the biggest new providers and it has partnered up with Graphiq. Graphiq is a service that uses AI to make data visualizations. There is faster access to data and the data can be updated regularly.
- Reducing the Human Element - AI can create compelling content without journalists’ help. It has the ability to create large masses of content because it can scan data and create an article based on that data in seconds, whereas it would take journalists hours. This does not mean journalists are not completely needed. With the correct usage of AI, compelling content can be created with the help of experienced journalists. A company that creates articles without experienced producers could lose some audience.
Disadvantages of AI in Journalism
- Data Availability - AI works best when there is sufficient data to analyze. It can look for patterns and find ways to optimize the system by learning from the data. If there isn’t a sufficient amount of data or even no data at all, it becomes hard for the system to learn, find patterns, and optimize itself. AI systems need millions of data points to function accurately.
- Unstructured Data - Tabulated forms of data or graphs are structured data. These forms of data can easily be interpreted by AI because it does not have to decode any information. For example, data from a sports game or the earnings of a company can be easily analyzed by AI. Data such as audio, video, or image files are unstructured and do not follow the standard template AI uses. Since the world has much more unstructured than structured data, AI needs to evolve so that it can interpret both types of data effortlessly.
- Authenticity - The input AI is given may not always be correct or valid. The sad thing is, AI cannot distinguish between invalid and valid forms of input. If there is a questionable input, there may be a wrong output. This results in false authenticity. To ensure authenticity, certain measures must be taken to prove it. This could include tracking back the information to its sources or journalists verifying the content.
Overall, AI has a lot of prospects in Journalism and can be a pretty useful tool for a lot of news companies. As AI systems can analyze data and create articles in seconds, companies can reach a wider audience in a short amount of time. AI not only helps in spreading news faster, but articles will have almost no errors in them, as AI is programmed to be almost perfect at what it does.